show_log=0)
packing_op = { #'target': '2byu',
'random_protein_number': 4,
'PDB_ori_path': 'IOfile/pdbfile/',
'iteration': 5001,
'step': 1,
'show_img': 0,
'show_log': 0,
'boundary_shpere': boundary_shpere
}
# convert pdb to map
import map_tomo.pdb2map as PM
import map_tomo.iomap as IM
ms = PM.pdb2map(op['map'])
for n in ms:
v = ms[n]
IM.map2mrc(v, op['map']['map_single_path'] + '/{}.mrc'.format(n))
print('convert pdb to map')
# read density map from mrc
rootdir = op['map']['map_single_path']
v = IM.readMrcMapDir(rootdir)
print('read density map done')
op['v'] = v
# generate subtomogram dataset
num = 0
for num in range(1000):
# '1w6t' '2bo9' '2gho' '3d2f' '1eqr' '1vrg' '3k7a' '1jgq' '1vpx'
def mknewdir(s1):
if not os.path.exists(s1):
os.makedirs(s1)
mknewdir('./IOfile/pdbfile/')
mknewdir('./IOfile/map_single')
mknewdir('./IOfile/json/')
mknewdir('./IOfile/packmap/target/mrc')
mknewdir('./IOfile/packmap/target/png')
mknewdir('./IOfile/tomo/target/mrc')
mknewdir('./IOfile/tomo/target/png')
# convert pdb file into single ball and get the center and radius of this ball.
boundary_shpere = P2B.pdb2ball_single(PDB_ori_path = 'IOfile/pdbfile/', show_log = 0)
packing_op = {#'target': '2byu',
'random_protein_number': 0,
'PDB_ori_path': 'IOfile/pdbfile/',
'iteration':5001,
'step':1,
'show_img': 0,
'show_log': 0,
'boundary_shpere': boundary_shpere
}
# convert pdb to map
import map_tomo.pdb2map as PM
import map_tomo.iomap as IM
ms = PM.pdb2map(op['map'])
for n in ms:
v = ms[n]
IM.map2mrc(v, op['map']['map_single_path']+ '/{}.mrc'.format(n))
print('convert pdb to map')
# read density map from mrc
rootdir = op['map']['map_single_path']
v = IM.readMrcMapDir(rootdir)
print('read density map done')
op['v'] = v
# generate subtomogram dataset
num = 0
for num in range(1000):
# '1w6t' '2bo9' '2gho' '3d2f' '1eqr' '1vrg' '3k7a' '1jgq' '1vpx'
# the above macromolecules may encounter some error
# set target macromolecule name
if num > 899:
packing_op['target'] = '3hhb'
elif num > 799:
packing_op['target'] = '2h12'
elif num > 699:
packing_op['target'] = '2ldb'
elif num > 599:
packing_op['target'] = '6t3e'
# else:
# pass
# # print(num, 'Pass')
elif num > 499:
packing_op['target'] = '4d4r'
elif num > 399:
packing_op['target'] = '3gl1'
elif num > 299:
packing_op['target'] = '2byu'
elif num > 199:
packing_op['target'] = '1yg6'
elif num > 99:
packing_op['target'] = '1f1b'
else:
packing_op['target'] = '1bxn'
if num >= 0:
print(num, packing_op['target'], 'start')
output = {
'initmap': {
'mrc': 'IOfile/initmap/mrc/initmap{}.mrc'.format(num),
'png': 'IOfile/initmap/png/initmap{}.png'.format(num),
'trim': 'Ofile/initmap/trim/initmap{}T.mrc'.format(num)},
'packmap': {
'mrc': 'IOfile/packmap/mrc/packmap{}.mrc'.format(num),
'png': 'IOfile/packmap/png/packmap{}.png'.format(num),
'trim': 'IOfile/packmap/trim/packmap{}T.mrc'.format(num),
'target': {
'mrc': 'IOfile/packmap/target/mrc/packtarget{}.mrc'.format(num),
'png': 'IOfile/packmap/target/png/packtarget{}.png'.format(num)}},
'tomo': {
'mrc': 'IOfile/tomo/mrc/tomo{}.mrc'.format(num),
'png': 'IOfile/tomo/png/tomo{}.png'.format(num),
'trim': 'IOfile/tomo/trim/tomo{}T.mrc'.format(num),
'target': {
'mrc': 'IOfile/tomo/target/mrc/tomotarget{}.mrc'.format(num),
'png': 'IOfile/tomo/target/png/tomotarget{}.png'.format(num)}},
'json': {
'pack': 'IOfile/json/packing{}.json'.format(num),
'target': 'IOfile/json/target{}.json'.format(num)}}
# do simulation
SS.simu_subtomo(op, packing_op, output, save_tomo=0, save_target=1, save_tomo_slice=0)
print(num, packing_op['target'], 'Done')
num = num + 1
print('all Done')
def simu_subtomo(op, packing_op, output, save_tomo = 0, save_target = 1, save_tomo_slice = 0):
'''
:param op: parameter of convert pdb/ density map to tomogram
:param packing_op: parameter of packing process
:param output: path of output file
:param save_tomo: 1 save, 0 not save, if the large subtomogram.mrc of the whole packing scene(including 5-10 macromolecules) will be saved
:param save_target: 1 save, 0 not save, if the subtomogram.mrc of the target will be saved
:param save_tomo_slice: 1 save, 0 not save, if the sliced image will be saved.
:return:
target_simu_tomo = { 'tomo' : subtomogram of target macromolecule, .mrc file
'density_map': density map, .mrc file
'info': { 'loc' : coordinate of target macromolecule
'rotate' : the rotation angle of this macromolecule (ZYZ, Euler angle)
'name' : the name of a macromolecule
}
}
the json file of packing result and target will be saved in '../IOfile/json'
'''
# convert pdb to map
import map_tomo.pdb2map as PM
import map_tomo.iomap as IM
ms = PM.pdb2map(op['map'])
for n in ms:
v = ms[n]
IM.map2mrc(v, op['map']['map_single_path']+ '/{}.mrc'.format(n))
# read density map from mrc
rootdir = op['map']['map_single_path']
v = IM.readMrcMapDir(rootdir)
# get packing info
import packing_single_sphere.simulate as SI
target_name = packing_op['target']
packing_result = SI.packing_with_target(packing_op)
protein_name = packing_result['optimal_result']['pdb_id']
x = packing_result['optimal_result']['x']/10
y = packing_result['optimal_result']['y']/10
z = packing_result['optimal_result']['z']/10
print('initialization',packing_result['optimal_result']['initialization'])
x0 = np.array(packing_result['optimal_result']['initialization'][0])/10
y0 = np.array(packing_result['optimal_result']['initialization'][1])/10
z0 = np.array(packing_result['optimal_result']['initialization'][2])/10
box_size = packing_result['general_info']['box_size']/10
# merge map to hugemap, save random angle in packing_result
import map_tomo.merge_map as MM
initmap,init_angle_list = MM.merge_map(v, protein_name, x0, y0, z0, box_size)
packmap,pack_angle_list = MM.merge_map(v, protein_name, x, y, z, box_size)
packing_result['optimal_result']['initmap_rotate_angle'] = init_angle_list
packing_result['optimal_result']['packmap_rotate_angle'] = pack_angle_list
# save packing info
with open(output['json']['pack'],'w') as f:
json.dump(packing_result, f, cls=MM.NumpyEncoder)
# convert packmap to tomogram
import map_tomo.map2tomogram as MT
tomo = MT.map2tomo(packmap, op['tomo'])
if save_tomo != 0:
# save init & pack map to mrc
IM.map2mrc(initmap, output['initmap']['mrc'])
IM.map2mrc(packmap, output['packmap']['mrc'])
# save init & pack map to png
IM.map2png(initmap, output['initmap']['png'])
IM.map2png(packmap, output['packmap']['png'])
#save pack tomo to mrc and png
IM.map2mrc(tomo, output['tomo']['mrc'])
IM.map2png(tomo, output['tomo']['png'])
# # trim hugemap
# trim_initmap = MM.trim_margin(initmap)
# trim_packmap = MM.trim_margin(packmap)
# trim_tomo = MM.trim_margin(tomo)
# print('initmap shape',initmap.shape)
# print('trimmed shape',trim_initmap.shape)
# print('packmap shape',packmap.shape)
# print('trimmed shape',trim_packmap.shape)
# print('tomo shape',tomo.shape)
# print('trimmed shape',trim_tomo.shape)
# IM.map2mrc(trim_initmap, output['initmap']['trim'])
# IM.map2mrc(trim_packmap, output['packmap']['trim'])
# IM.map2mrc(trim_tomo, output['tomo']['trim'])
# trim target
i = protein_name.index(target_name)
print('i',i)
target_packmap, loc_r = MM.trim_target(packmap, np.array([x[i],y[i],z[i]]), op['target_size'])
target_tomo, loc_r = MM.trim_target(tomo, np.array([x[i],y[i],z[i]]), op['target_size'], loc_r)
if save_target != 0:
IM.map2mrc(target_packmap, output['packmap']['target']['mrc'])
IM.map2mrc(target_tomo, output['tomo']['target']['mrc'])
IM.map2png(target_packmap, output['packmap']['target']['png'])
IM.map2png(target_tomo, output['tomo']['target']['png'])
# save target info
target_info = {}
target_info['loc'] = loc_r
target_info['rotate'] = pack_angle_list[i]
target_info['name'] = packing_op['target']
with open(output['json']['target'],'w') as f:
json.dump(target_info, f, cls=MM.NumpyEncoder)
if save_tomo_slice != 0:
# convert packmap & tomo to separate pictures
import map_tomo.mrc2singlepic as MS
MS.mrc2singlepic(output['packmap']['mrc'], output['packmap']['png'] + 'packmap{}/'.format(num), 'packmap{}'.format(num))
MS.mrc2singlepic(output['tomo']['mrc'], output['tomo']['png'] + 'tomo{}/'.format(num), 'tomo{}'.format(num))
target_simu_tomo = {}
target_simu_tomo['tomo'] = target_tomo
target_simu_tomo['density_map'] = target_packmap
target_simu_tomo['info'] = target_info
return target_simu_tomo